Reliability is key for a core banking platform. In this post I will give you some learnings and insights into a successful core banking performance engineering strategy.
Clarify defect tracking process and responsibilities upfront
Agree on deployment slots for your test environment
Data sets can have massive impact on end to end response times. Make sure that data volumes, roles and permissions are in line with current production.
Carefully check response time, throughput and data volume requirements.
Non-functional requirements are key for a successful load and performance test. Focus your efforts on NFRs and once they are approved start with production like load and performance test execution.
Weekly status reports are a must. Make sure that content is aligned with other streams and report overall status, defects, test execution progress and blocking issues regularly.
Fundamental performance engineering approach
Conduct Performance Risk Assessment to identify the scope
Specify performance requirements
Document test approach
Real browser based end-to-end use cases
API based web service requests
Manage test data, permissions and infrastructure constraints
Benchmarking of Base Stack Infrastructure
Single application tests
Combined tests to simulate production load on all apps at the same time
Actual and future growth patterns
Create test reports in lightweight wiki pages
Focus on key performance metrics
Agreed on defect assignment rules
Use tags for your defects tracking
Created reporting dashboards
Bi-weekly defect review sessions
Performance Testing – Silk Performer, SilkCentral
Performance Monitoring – dynatrace
Synthetic Monitoring – Silk Performance Manager
Defect Tracking – Jira
Reporting – Confluence and Sharepoint
Test Management – Spira
This full list of learnings and advices will help you in your next performance engineering project to identify hotspots quickly without jumping in too many pitfalls.